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» A Problem Kernelization for Graph Packing
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ICML
2007
IEEE
14 years 8 months ago
Gradient boosting for kernelized output spaces
A general framework is proposed for gradient boosting in supervised learning problems where the loss function is defined using a kernel over the output space. It extends boosting ...
Florence d'Alché-Buc, Louis Wehenkel, Pierr...
BMCBI
2008
149views more  BMCBI 2008»
13 years 7 months ago
All-paths graph kernel for protein-protein interaction extraction with evaluation of cross-corpus learning
Background: Automated extraction of protein-protein interactions (PPI) is an important and widely studied task in biomedical text mining. We propose a graph kernel based approach ...
Antti Airola, Sampo Pyysalo, Jari Björne, Tap...
CIKM
2009
Springer
14 years 2 months ago
L2 norm regularized feature kernel regression for graph data
Features in many real world applications such as Cheminformatics, Bioinformatics and Information Retrieval have complex internal structure. For example, frequent patterns mined fr...
Hongliang Fei, Jun Huan
IJCAI
2003
13 years 9 months ago
Continuous nonlinear dimensionality reduction by kernel Eigenmaps
We equate nonlinear dimensionality reduction (NLDR) to graph embedding with side information about the vertices, and derive a solution to either problem in the form of a kernel-ba...
Matthew Brand
STOC
2003
ACM
133views Algorithms» more  STOC 2003»
14 years 7 months ago
A fast algorithm for computing steiner edge connectivity
Given an undirected graph or an Eulerian directed graph G and a subset S of its vertices, we show how to determine the edge connectivity C of the vertices in S in time O(C3 n log ...
Richard Cole, Ramesh Hariharan